Nebula: Ultra-efficient mapping-free structural variant genotyper

Parsoa Khorsand, Fereydoun Hormozdiari

Research output: Contribution to journalArticlepeer-review

Abstract

Large scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping complex events. We are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches. Our method Nebula utilizes the changes in the count of k-mers to predict the genotype of structural variants. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping structural variants, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event. Nebula is publicly available at http://github.com/Parsoa/Nebula.

Original languageEnglish (US)
Pages (from-to)E47
JournalNucleic acids research
Volume49
Issue number8
DOIs
StatePublished - May 7 2021

ASJC Scopus subject areas

  • Genetics

Fingerprint

Dive into the research topics of 'Nebula: Ultra-efficient mapping-free structural variant genotyper'. Together they form a unique fingerprint.

Cite this